Import Dataset and create working dataset:
#install.packages("plotly")
library(plotly)
package 㤼㸱plotly㤼㸲 was built under R version 4.0.4Registered S3 method overwritten by 'data.table':
method from
print.data.table
Registered S3 method overwritten by 'htmlwidgets':
method from
print.htmlwidget tools:rstudio
Attaching package: 㤼㸱plotly㤼㸲
The following object is masked from 㤼㸱package:ggplot2㤼㸲:
last_plot
The following object is masked from 㤼㸱package:stats㤼㸲:
filter
The following object is masked from 㤼㸱package:graphics㤼㸲:
layout
game_melt %>%
group_by(Region,Year,Genre) %>%
summarise(net = sum(`Copies Sold`))
`summarise()` regrouping output by 'Region', 'Year' (override with `.groups` argument)
Graph time baby!
#Number of Copies Sold
library(tidyverse)
graph1 <- game_melt %>%
filter(Region == "NA_Sales") %>%
group_by(Region,Year,Genre) %>%
summarise("Copies Sold" = sum(`Copies Sold`)) %>%
ggplot() +
aes(x=Year,
y=`Copies Sold`,
fill = Genre) +
geom_bar(stat="identity")+
theme(axis.text.x = element_text(angle = 90, hjust=0.95, vjust=0.2))+
ylab("Number of Copies Sold (in millions)")
`summarise()` regrouping output by 'Region', 'Year' (override with `.groups` argument)
ggplotly(graph1)
#Number of Copies Sold
library(tidyverse)
graph2 <- game_melt %>%
filter(Region == "NA_Sales") %>%
group_by(Region,Year,Genre) %>%
count(Year,Genre) %>%
rename(`Number of Releases`="n")%>%
ggplot() +
aes(x=Year,
y=`Number of Releases`,
fill = Genre) +
geom_bar(stat="identity")+
theme(axis.text.x = element_text(angle = 90, hjust=0.95, vjust=0.2))+
ylab("Number of games released")
ggplotly(graph2)
#Number of Platforms, Genres and Publishers with games > 100 copies sold
graph3 <- game_melt %>%
filter(Region == "JP_Sales") %>%
group_by(Year)%>%
melt(id.vars=c("Year"),measure.vars=c("Genre","Platform","Publisher")) %>%
rename(Category='variable') %>%
group_by(Year,Category) %>%
unique() %>%
count(Year,Category) %>%
rename(`Counts of Genres, Publishers and Platforms`= n) %>%
ggplot() +
aes(x=Year,
y=`Counts of Genres, Publishers and Platforms`,
fill = Category) +
geom_bar(stat="identity")+
theme(axis.text.x = element_text(angle = 90, hjust=0.95, vjust=0.2))+
ylab("Counts of Genres, Publishers and Platforms")
ggplotly(graph3)
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